Data is often referred to as the new oil of the digital economy, representing a highly valuable and untapped asset. To fully realize the potential of spatial data, various spatial data marketplace platforms have emerged. The existing spatial data marketplaces primarily focus on recommending each dataset individually. There is a lack of consideration for cases where an individual dataset cannot satisfy the buyer’s needs such that a collection of datasets needs to be acquired.

Researchers from BUPT introduce the RFGDG framework,utilizing RL to dynamically optimize graph generalization in federated settings.

Prompt engineering has emerged as a critical tool to refine AI outputs, but existing techniques are fragmented and lack a cohesive structure. The research team, led by Professor Feng Zhang from Renmin University of China and collaborators from Microsoft AI, Tsinghua University, and the National University of Singapore, published their new research on 15 March 2026 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature.

Promoting the development and application of more accurate, ethically responsible artificial intelligence tools adapted to real clinical needs in order to improve the quality of healthcare is one of the main objectives of the NursIA network, an initiative led by a multidisciplinary team at the Universitat Jaume I in Castelló. The network brings together five research groups in fields such as nursing, biostatistics, machine learning, process mining and applied ethics, with the aim of contributing to the transformation of healthcare through innovative AI-based solutions that improve patient safety and the efficiency of healthcare processes.

Funded by the Universitat Jaume I’s 2025–2026 programme for the promotion of research and knowledge transfer, the network aims to generate impact in three key areas: scientific and technical development, institutional collaboration and knowledge transfer, and communication and outreach. Planned activities include a conference on the practical implementation of AI in clinical environments, the first open NursIA conference on artificial intelligence and healthcare transformation, and several scientific publications on AI applied to healthcare.

More than seventy years after Alan Turing posed the question of whether machines could think, advances in artificial intelligence have shifted the focus from imitation to collaboration. As AI increasingly undertakes complex academic tasks through multi-agent collaboration, a new question emerges: beyond the Turing Test, how should the human role in research be redefined?

Atomic clocks based on entangled atoms can reach extremely high precision but usually suffer from a limited measurement range. Researchers have proposed a new adaptive Bayesian protocol that dynamically adjusts measurement time using prior information. This approach allows GHZ-state atomic clocks to maintain Heisenberg-limited precision while significantly expanding their dynamic range. Simulations show improved accuracy, faster convergence, and stronger resistance to noise. The method offers a powerful framework for next-generation atomic clocks and other quantum sensors requiring both high precision and broad measurement capability.

Researchers at Aarhus University report a proof-of-concept DNA needle inspired by bacteriophages that can deliver molecules directly into cells and help them remain active. In laboratory experiments, the structure avoided endosomal trapping, a major limitation in current delivery methods. The approach may support future development of RNA-based therapies and treatments for rare genetic disorders.